Unlock performance and behavior insights
Combine data to analyze content engagement, viewer patterns, ad performance, and risk — all through SQL queries powered by Coactive’s Dynamic Tags and Concepts.
Gain actionable insights from your content library
Coactive’s SQL analysis capabilities let teams query, filter, and evaluate large-scale visual datasets—enabling precise, programmatic insights across content performance, behavior, and risk.
Advanced analytics
Rich, multi-signal analysis
Filter and combine transcript, visual, and audio signals to uncover deeper trends across content libraries.
Export-ready for external evaluation
Send structured outputs (e.g., raw tag scores, probabilities) to S3 or CSV. These exports can be easily loaded into Python, R, or PySpark for experiments, scoring, and fine-tuning.
Run cross-database queries to compare ad performance by content type
Visual data analytics
Transform unstructured visual data into actionable analytics through SQL queries.
Ad performance analysis
Compare and analyze metadata from custom classifications (powered by Coactive) with ad data to understand which creative or content types perform best.
Cross-system queries
Aggregate data via APIs across multiple storage systems and generate optimized, cross-database queries.
Seamless export into BI/analytics tools
Easily push Coactive data into warehouses or data lakes (e.g., Delta Lake) and analyze it alongside key performance metrics in your existing BI stack.
Gain powerful insights - combine Coactive data with other datasets
Gain powerful insights by blending Coactive data and metadata with your ratings, ad, audience, or other data.
Content performance
Measure audience retention on Olympic highlights vs. scripted drama, or compare drop-off between live and on-demand shows.
Audience behavior
Track how viewers engage differently with sports, news, and entertainment across platforms.
Ad effectiveness
Compare campaign performance across sports vs. entertainment programming, to see where ads drive the most lift.
Risk assessment
Flag high-risk content segments — from inappropriate moments in children’s shows to sensitive issues in live broadcasts.
SQL analysis capabilities
Filter and flag content at scale
Quickly remove profanity, violence, or other sensitive content across millions of clips with a single query.
Combine ratings and metadata
Aggregate ratings data with content metadata to identify which storylines, scenes, or ad placements drive audience spikes or drops.
Optimize ad and promo strategies
Analyze ad performance across different genres and time slots to refine targeting and scheduling.
Enable downstream experimentation
Export clean, structured outputs into S3, Python, R, or PySpark for advanced modeling, testing, or audience analysis.
Understand performance and run data-driven experiments
Export data for validation
Download probability and score data to external tools like PySpark or Excel to test thresholds and validate results.
Benchmark performance across content
For example, compare cut-sheet performance data across networks or campaigns to identify which content drives higher ratings, engagement, or ad effectiveness.
Run advanced experiments
Use raw tag score data in Python or R to experiment with new models, evaluate promo effectiveness across genres, or test metadata thresholds for trust and safety.
Coactive automatically generates additional metadata on the backend that becomes accessible via SQL queries for calculated evaluations.
